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Strong LP Formulations for Scheduling Splittable Jobs on Unrelated Machines

Publications associées (55)

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Applications of Strong Convex Relaxations to Allocation Problems

Christos Kalaitzis

Approximation algorithms are a commonly used tool for designing efficient algorithmic solutions for intractable problems, at the expense of the quality of the output solution. A prominent technique for designing such algorithms is the use of Linear Program ...

EPFL2017

LP-Based Algorithms For Capacitated Facility Location

Ola Nils Anders Svensson, Hyung Chan An

Linear programming (LP) has played a key role in the study of algorithms for combinatorial optimization problems. In the field of approximation algorithms, this is well illustrated by the uncapacitated facility location problem. A variety of algorithmic me ...

Society for Industrial and Applied Mathematics2017

Efficient Linear Programming for Dense CRFs

Mathieu Salzmann

The fully connected conditional random field (CRF) with Gaussian pairwise potentials has proven popular and effective for multi-class semantic segmentation. While the energy of a dense CRF can be minimized accurately using a linear programming (LP) relaxat ...

2017

Group-Sparse Model Selection: Hardness and Relaxations

Volkan Cevher, Anastasios Kyrillidis, Luca Baldassarre, Nirav Bhan

Group-based sparsity models are proven instrumental in linear regression problems for recovering signals from much fewer measurements than standard compressive sensing. The main promise of these models is the recovery of ``interpretable" signals along with ...

Institute of Electrical and Electronics Engineers2016

Strong LP formulations for scheduling splittable jobs on unrelated machines

Ola Nils Anders Svensson

A natural extension of the makespan minimization problem on unrelated machines is to allow jobs to be partially processed by different machines while incurring an arbitrary setup time. In this paper we present increasingly stronger LP-relaxations for this ...

Springer Heidelberg2015

A totally unimodular view of structured sparsity

Volkan Cevher, Marwa El Halabi

This paper describes a simple framework for structured sparse recovery based on convex optimization. We show that many interesting structured sparsity models can be naturally represented by linear matrix inequalities on the support of the unknown parameter ...

2015

No Small Linear Program Approximates Vertex Cover within a Factor 2 - e

Ola Nils Anders Svensson, Abbas Bazzi

The vertex cover problem is one of the most important and intensively studied combinatorial optimization problems. Khot and Regevproved that the problem is NP-hard to approximate within a factor2 - ∈, assuming the Unique Games Conjecture (UGC). This is tig ...

IEEE Computer Society2015

A Tight Linear Time (1/2)-Approximation For Unconstrained Submodular Maximization

Moran Feldman

We consider the Unconstrained Submodular Maximization problem in which we are given a nonnegative submodular function f : 2(N) -> R+, and the objective is to find a subset S subset of N maximizing f(S). This is one of the most basic submodular optimization ...

Siam Publications2015

Node-weighted network design and maximum sub-determinants

Carsten Moldenhauer

We consider the Node-weighted Steiner Forest problem on planar graphs. Demaine et al. showed that a generic primal-dual algorithm gives a 6-approximation. We present two different proofs of an approximation factor of~

3

. Then, we draw a connection to Goem ...

EPFL2014

Coding Structure and Replication Optimization for Interactive Multiview Video Streaming

Pascal Frossard

Multiview video refers to videos of the same dynamic 3-D scene captured simultaneously by multiple closely spaced cameras from different viewpoints. We study interactive streaming of pre-encoded multiview videos, where, at any time, a client can request an ...

Ieee-Inst Electrical Electronics Engineers Inc2014

Node-weighted network design and maximum sub-determinants

Carsten Moldenhauer

3

. Then, we draw a connection to Goem ...

EPFL2014